Inverse problem of spectral reflection prediction by artificial neural networks: Preliminary results

Digital image processing requires substantial computations during characterization. Most of color prediction models require mathematical apparatus to predict spectral reflectance for a mixture of colorants that have been characterized by absorption and scattering during light propagation. However, few attempts were made to make a model for prediction of colorants values from an observing spectrum. This work devoted to application of artificial neural network approach for solving the inverse problem of spectral reflection prediction. Our attempt is based on the assumption that the prediction of the initial colorants from spectral data is possible by analogy with the work of the color perception system in humans. The model is built in Matlab and shows satisfactory accuracy of prediction.